Readme for data repository for "Did Karl Marx Party in 1891?" by Phillip Magness and Michael Makovi

Instructions: 
(1) Install Stata and R.
(2) Unzip this ZIP file to any arbitrary disk location. Executing "\do files\2 - Synth regressions.do" will create a “results” folder in the same relative location as the “do files” folder.
(3) A list of necessary Stata packages and the code to install them, is found at the beginning of "\do files\2 - Synth regressions.do".

To generate the primary output, run "\do files\2 - Synth regressions.do" followed by "\do files\3 - meta p-values.do". The results are output to "\results\".

Note that our SCM regressions require 512 GB of RAM. If your system does not have this much RAM, you will only be able to obtain approximately similar results. To do this, open "\do files\2 - Synth regressions.do" and change the following line:
	Line 98: global convergence = "nested allopt technique(dfp) maxiter(30)" 
	becomes: global convergence = "technique(dfp)"
This will cause synth to use the default, non-nested procedure, in which the V-matrix is estimated by a regression and then held fixed. The W-matrix is optimized with respect to this fixed V-matrix. The results will not be identical to those reported in the paper, but they will be very similar.

There are 4 Stata do files, located in \do files\:
1) "1 - Scrape German newspapers.do" --- generates "\data files\german_newspaper_data_w_indicators.dta"
2) "2 - Synth regressions.do" --- the primary do file to generate all results, which are output to the "\results\" folder
3) "3 - meta p-values.do" --- generates meta p-values, to meta-analyze p-values from this paper and its prequel ("The Mainstreaming of Marx"), as reported in the present paper
4) "save_synth_and_synth_runner.output.do" --- an auxiliary file used to save results to disk

There are several data files, located in \data files\:
1) "all_authors_with_citations_and_indicators.dta" --- the original data file from Magness and Makovi, "The Mainstreaming of Marx," available in its own Harvard Dataverse repository, and duplicated here
2a) "Marx_author_indicators - additional authors.xlsx" and 
2b) "Marx1850-2000_Gram - additional authors.xlsx" 
--- Google Ngram data and indicator variable data for additional authors used in this paper
3) "german_newspaper_data_w_indicators.dta" --- output from "\do files\1 - Scrape German newspapers.do", containing citation data from German newspapers
4a) "KarlKautsky.dta" and 
4b) "additional_authors.dta" 
--- output from "do files\2 - Synth regressions.do" using "Marx_author_indicators - additional authors.xlsx" and "Marx1850-2000_Gram - additional authors.xlsx", containing citation and indicator data for additional authors




 